Showing papers from Google Deepmind / Harvard Show all papers
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Equilibrium Matching learns implicit energy landscapes for optimization-based sampling, surpassing diffusion models with 1.90 FID on ImageNet 256x256 while supporting denoising, OOD detection, and composition.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 7 on Hugging Face · Code ★ 217
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Equilibrium Forcing removes noise conditioning from video diffusion to enable adaptive closed-loop inference that improves generation quality and consistency.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Masked Visual Actions expresses robot and object motion as revealed pixel trajectories to unify forward dynamics, planning, and inverse modeling in video world models with minimal finetuning.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 9 on Hugging Face · Code ★ 110
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Temporal Backtracking Search improves video reasoning by searching over the temporal axis and restarting from verified prefixes rather than resampling from scratch, achieving 22.7% versus 0.7% best-of-N out-of-distribution.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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SyncWorld learns action-visual mappings via visual calibration episodes to serve as zero-shot simulators across unseen robot settings without retraining.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 16 on Hugging Face · Code ★ 21
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Action Images formulates robot policy learning as multiview video generation using interpretable pixel-grounded action images, enabling zero-shot control without separate policy heads and improving video-action joint generation.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 8 on Hugging Face
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MoSE3 predicts dense per-pixel world-space SE(3) motion from monocular video via point tracks and rigidity embeddings, achieving state-of-the-art 6-DoF estimation and 3D tracking.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 1 on Hugging Face
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